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      Model aversiveness and the evolution of imperfect Batesian mimics

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          Abstract

          There are numerous examples in the natural world of Batesian mimics that only imperfectly resemble their models. Given that inaccurate mimics are known to be predated more frequently than accurate ones, imperfect mimicry therefore poses something of a conundrum. One putative explanation, the relaxed selection hypothesis, predicts that when the cost of attacking a model is high relative to the benefit of consuming a mimic, selection against imperfect mimics will be relaxed, allowing mimics to be more imperfect for a given level of fitness. However, empirical support for this hypothesis is equivocal. Here we report an experimental test of the relaxed selection hypothesis, in which human participants were tasked with discriminating between artificial stimuli representing models and mimics. In response to ‘attacking’ a model (i.e., misclassifying it as palatable, or non-aversive) they received either a mild electric shock (high cost) or vibratory feedback (low cost). Consistent with the predictions of this hypothesis, we found that when the cost of attacking a model was high, mimetic phenotype could deviate more from the model (i.e., be more imperfect) for a given level of fitness than when the cost of attacking a model was low. Moreover, when the cost of attacking a model was high, participants showed an increased latency to attack. This finding shows that given sufficient costs, the relaxed selection hypothesis is a plausible explanation for the evolution of imperfect mimicry within certain ecological contexts.

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          Author and article information

          Journal
          Dryad
          2023
          17 July 2023
          17 July 2023
          Affiliations
          [1 ] University of Lincoln
          Author information
          https://orcid.org/0000-0002-6942-0498
          Article
          10.5061/DRYAD.NP5HQC003
          17979599-4980-4de0-94d9-fa7e6e6cec48

          CC0 1.0 Universal (CC0 1.0) Public Domain Dedication

          History

          FOS: Biological sciences,Predation,colour pattern,adaptation,Batesian mimicry

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